Geology topics

Lillian E. Gorman Sanisaca

Publications and source records attributed to Lillian E. Gorman Sanisaca.

10 recordsLinked to original sources

USGS2025

Water withdrawal and consumption trends for thermoelectric-power plants in the conterminous United States, 2008-2020

Freshwater-using utility-scale thermoelectric (TE) plant water-use estimates were evaluated for annual trends from 2008 to 2020 across the conterminous United States (CONUS) and within hydrologic regions. Overall, TE water withdrawal and consumption trends declined across CONUS by 14,335 and 278 million liters/day, respectively. Decreasing water withdrawal and consumption trends for TE plants are driven largely by switching from coal-fired plants to other generation technologies. TE plant cooling system technology has also changed, with large declining trends for TE plants using once-through cooling systems and small increasing consumption trends for TE plants using recirculating tower cooling systems. Fifteen hydrologic regions have decreasing trends in withdrawals and consumption. The largest decreases are for coal-fired plants using once-through freshwater cooling systems in the Great Lakes and Ohio hydrologic regions. Natural gas combined cycle plants with recirculating tower cooling systems have increased water consumption trends across most of the CONUS hydrologic regions. Some TE plants with recirculating tower or once-through cooling systems withdraw water volumes that on average are close to or exceed average simulated streamflows. Most of these situations occur in the central and eastern U.S., potentially leading to water availability issues among competing water needs, ecosystem impacts from thermal pollution, and power generation constraints.

conterminous United States↗

USGS2025

Automating physics-based models to estimate thermoelectric-power water use

Thermoelectric (TE) power plants withdraw more water than any other sector of water use in the United States and consume water at rates that can be significant especially in water-stressed regions. Historical TE water-use data have been inconsistent, incomplete, or discrepant, resulting in an increased research focus on improving the accuracy and availability of TE water-use data using modeling approaches. This paper describes and benchmarks new code that was developed to automate and update a physics-based TE water use model that was previously published. Utilizing the automated physics-based model, monthly TE-power water withdrawal and consumption were calculated for a total of 1341 TE power plants for the 2008–2020 historical reanalysis. The updated and automated physics-based thermoelectric-power water-use model provides spatially and temporally relevant TE water-use estimates that are consistent, reproducible, transparent, and can be generated efficiently for water-using, utility-scale TE-power plants across conterminous United States (CONUS).

Environmental Modelling and Software↗

USGS2020

Application of the RSPARROW modeling tool to estimate total nitrogen sources to streams and evaluate source reduction management scenarios in the Grande River Basin, Brazil

Large-domain hydrological models are increasingly needed to support water-resource assessment and management in large river basins. Here, we describe results for the first Brazilian application of the SPAtially Referenced Regression On Watershed attributes (SPARROW) model using a new open-source modeling and interactive decision support system tool (RSPARROW) to quantify the origin, flux, and fate of total nitrogen (TN) in two sub-basins of the Grande River Basin (GRB; 43,000 km 2 ). Land under cultivation for sugar cane, urban land, and point source inputs from wastewater treatment plants was estimated to each contribute approximately 30% of the TN load at the outlet, with pasture land contributing about 10% of the load. Hypothetical assessments of wastewater treatment plant upgrades and the building of new facilities that could treat currently untreated urban runoff suggest that these management actions could potentially reduce loading at the outlet by as much as 20–25%. This study highlights the ability of SPARROW and the RSPARROW mapping tool to assist with the development and evaluation of management actions aimed at reducing nutrient pollution and eutrophication. The freely available RSPARROW modeling tool provides new opportunities to improve understanding of the sources, delivery, and transport of water-quality contaminants in watersheds throughout the world.

Grande River basin↗

USGS2020

Monthly suspended-sediment apportionment for a western Lake Erie agricultural tributary

Black Creek, a headwater to the Maumee River and western Lake Erie, is an agricultural basin with a mix of cropland (66%), pasture (19%), and forest (7%) linked by a road network to the rural community. Suspended sediment was collected monthly during the 2018 water year for the main stem and two sub-basins using in-situ, passive samplers that integrated a range of streamflow conditions. Sediment fingerprinting used 44 indicators to apportion samples among five sources: cropland, pasture, forest, road dirt, and streambanks. Cropland, pasture, and streambanks had similar ranges in sediment-bound phosphorus (679-1670 ppm). Cropland contributed 21 ± 15% (monthly mean ± standard deviation; 0-46% among individual months) of suspended sediment during the year. Fall and spring peaks in cropland contribution highlight the ongoing importance of on-field management, but this small contribution of suspended sediment relative to the expanse of cropland may reflect implementation of best-management practices. Pasture contributed 0-66% (16±19%) of suspended-sediment and roads 0-26% (6±6%). Streambanks contributed 12-100% (55±25%) and was the only source identified in all sediment samples. In this basin, most cropland-adjacent streambanks are protected by a riparian setback. However, streams traversing other land-use types are not as consistently protected, and these setbacks do not protect the stream channel from discharge of water from sump pumps, road culverts, or tile drains. The contribution of sediment from other land uses combined with that from the agricultural drainage network (as streambank material) underscores the need to consider water movement in the basin as a whole.

Indiana↗

USGS2019

Annual wastewater nutrient data preparation and load estimation using the Point Source Load Estimation Tool (PSLoadEsT)

The Point-Source Load Estimation Tool (PSLoadEsT) provides a user-friendly interface for generating reproducible load calculations for point source dischargers while managing common data challenges including duplicates, incompatible input tables, and incomplete or missing nutrient concentration or effluent flow data. Maintaining a consistent method across an entire study area is important when estimating loads to be used as calibration data for regional water-quality models. PSLoadEsT is written using the open-source programming language R and has an easy-to-use interface written in Visual Basic for Applications® within a Microsoft Access® database file that guides the user through the necessary steps to estimate point source loads. The purpose of this report is to provide a detailed user guide for PSLoadEsT.

Open-File Report↗

USGS2018

Sediment source assessment using sediment fingerprints

Problem Sediment is one of the most common causes of loss of stream-biologic integrity, whether in suspension in the water column, or as deposition on a stream or lake bottom. Fine-grained silts and clays are of particular concern because they can degrade habitat and often carry phosphorus and (or) other contaminants harmful to humans and aquatic life. Sediment-impaired water bodies, usually identified by fair to poor macroinvertebrate index scores, are placed on the 303(d) list of impaired waters, where a sediment Total Maximum Daily Load (TMDL) is developed under the Clean Water Act ( https://www.epa.gov/tmdl ). In order to effectively manage sediment, it is necessary to identify the sediment sources and locations of “hot spots” of erosion and deposition.

Fact Sheet↗

USGS2018

Sediment fingerprinting to delineate sources of sediment in the agricultural and forested Smith Creek Watershed, Virginia, USA

The sediment fingerprinting approach was used to apportion fine‐grained sediment to cropland, pasture, forests, and streambanks in the agricultural and forested Smith Creek, watershed, Virginia. Smith Creek is a showcase study area in the Chesapeake Bay watershed, where management actions to reduce nutrients and sediment are being monitored. Analyses of suspended sediment at the downstream and upstream sampling sites indicated streambanks were the major source of sediment (76% downstream and 70% upstream). Current management strategies proposed to reduce sediment loadings for Smith Creek do not target streambanks as a source of sediment, whereas the results of this study indicate that management strategies to reduce sediment loads in Smith Creek may be effective if directed toward managing streambank erosion. The results of this study also highlight the utility of sediment fingerprinting as a management tool to identify sediment sources.

Virginia↗

USGS2018

Bank‐derived material dominates fluvial sediment in a suburban Chesapeake Bay watershed

Excess fine sediment is a leading cause of ecological degradation within the Chesapeake Bay watershed. To effectively target sediment mitigation measures, it is necessary to identify and quantify the delivery of sediment sources to local waterbodies. This study examines the contributions of sediment sources within Upper Difficult Run, a suburbanized watershed in Fairfax County, Virginia. A source sediment library was constructed from stream banks, forest soils, and road dust. Target sediments were collected from fine channel deposits and suspended sediment during 16 storm events from 2008 to 2012. Apportionment of targets to sources was performed using Sed_SAT, a publicly available toolkit for sediment fingerprinting. Bed sediment was dominated by stream bank material (mean: 98%), with minor contributions from forests (2%). Suspended fine sediments were also dominated by stream banks (suspended sediment concentration‐weighted mean: 91%), with minor contributions from roads (8%) and forests (<1%). Stream banks dominated at all discharges, and on the rising limb and at peak flow, sediment concentrations increased due to bank material rather than surface erosion. Sediment budget data indicated that direct bank erosion was insufficient to account for the suspended load derived from stream banks. However, bank‐derived sediment re‐mobilized from in‐channel storage could account for this difference and, combined, resulted in a sediment delivery ratio of 0.847 for all bank‐derived sediments. Results demonstrate that stream bank erosion is responsible for the majority of fine sediment in this suburban watershed of the Chesapeake Bay drainage area. Thus, management actions to control upland sources of sediment may have limited effect on the sediment conditions of Upper Difficult Run, whereas efforts focusing on bank stabilization, channel restoration, and/or stormwater management to reduce bank erosion may improve the ecological condition of these waterbodies.

Virginia↗

USGS2017

Determining the sources of fine-grained sediment using the Sediment Source Assessment Tool (Sed_SAT)

A sound understanding of sources contributing to instream sediment flux in a watershed is important when developing total maximum daily load (TMDL) management strategies designed to reduce suspended sediment in streams. Sediment fingerprinting and sediment budget approaches are two techniques that, when used jointly, can qualify and quantify the major sources of sediment in a given watershed. The sediment fingerprinting approach uses trace element concentrations from samples in known potential source areas to determine a clear signature of each potential source. A mixing model is then used to determine the relative source contribution to the target suspended sediment samples. The computational steps required to apportion sediment for each target sample are quite involved and time intensive, a problem the Sediment Source Assessment Tool (Sed_SAT) addresses. Sed_SAT is a user-friendly statistical model that guides the user through the necessary steps in order to quantify the relative contributions of sediment sources in a given watershed. The model is written using the statistical software R (R Core Team, 2016b) and utilizes Microsoft Access® as a user interface but requires no prior knowledge of R or Microsoft Access® to successfully run the model successfully. Sed_SAT identifies outliers, corrects for differences in size and organic content in the source samples relative to the target samples, evaluates the conservative behavior of tracers used in fingerprinting by applying a “Bracket Test,” identifies tracers with the highest discriminatory power, and provides robust error analysis through a Monte Carlo simulation following the mixing model. Quantifying sediment source contributions using the sediment fingerprinting approach provides local, State, and Federal land management agencies with important information needed to implement effective strategies to reduce sediment. Sed_SAT is designed to assist these agencies in applying the sediment fingerprinting approach to quantify sediment sources in the sediment TMDL framework.

Open-File Report↗

USGS2015

Identifying sediment sources in the sediment TMDL process

Sediment is an important pollutant contributing to aquatic-habitat degradation in many waterways of the United States. This paper discusses the application of sediment budgets in conjunction with sediment fingerprinting as tools to determine the sources of sediment in impaired waterways. These approaches complement monitoring, assessment, and modeling of sediment erosion, transport, and storage in watersheds. Combining the sediment fingerprinting and sediment budget approaches can help determine specific adaptive management plans and techniques applied to targeting hot spots or areas of high erosion.

Conference Paper↗